Associate - Assurance, Forensic - Data Analytics

Your Key Responsibilities:

• Work with clients, fraud investigators, internal and external auditors, lawyers and regulatory authorities in sensitive situations and assist on conducting data analysis for identifying evidences of fraud, abuse and wastage.
• Analyse and mine the data using different analytical techniques to identify both known and unknown patterns of fraud.
• Collect and analyse a large amount of structured and unstructured data from a variety of data sources including ERP systems, accounting systems and others.
• Carry out both reactive and proactive data analysis of large datasets using a wide range of technologies, database management systems, business information reporting and visualisation software.
• Develop algorithms and solutions to detect, respond, prevent, continually monitor and investigate areas of fraud, bribery & corruption, misconduct and financial crime.
• Develop supporting material using a suite of visualisation software to clearly present the benefits of the analysis to clients.
• Execute end-to-end lifecycle of the engagement - Data extraction, transformation, loading (ETL), analysis, visualisation, deployment and client delivery.
• Align to various strategic teams in the areas of technology and innovation

Skills and Attributes for Success:

• Strong academic qualifications with a degree in a STEM discipline (Computer Science, Engineering, Statistics, Mathematics, etc.) or equivalent work experience.
• Demonstrate proficiency in SQL and a broad awareness of programming languages such as Python, R as well as Visualization techniques.
• Strong problem solving, analytical, technical, and interpersonal skills.
• Strong critical thinking, problem-solving skills, understanding of algorithms and appreciation of working with data.
• Excellent communication skills and ability to explain complex analytical concepts to stakeholders from different backgrounds.
• Excellent documentation skills with the ability to prioritize when working on multiple engagements.
• The ability to travel to client locations.
• Previous consulting experience and experience with any of the below areas would be an added benefit:
• Relational databases, e.g. SQL Server, PostgreSQL, Oracle, MySQL;
• Data visualisation software: Spotfire, Tableau, or Power BI;
• Azure/AWS cloud computing platform;
• Big data technologies such as Spark, Elasticsearch, Hadoop;
• Statistical techniques (regression, clustering etc.);
• Machine learning, pattern recognition, NLP etc.